- [Instructor] Dplyer is a member of…the tidyverse ecosystem…and designed for manipulating data…with a variety of different verbs.…The group by verb allows data to be categorized…into a hierarchy of groups.…For instance, data could be grouped by…continent, country, and then city.…Dplyr operations like filtering, sampling,…or calculating values using mutate…can be done within these groups.…It's important to note that groups…are a special feature of the tidyverse's…version of a data frame, the tibble.…

For most intents and purposes,…we call tibbles data frames.…But I thoroughly recommend you understand…the relationship between tibbles and data frames…if you're going to be a hardcore user…of group by and dplyr.…Let's look at some examples of using group by…inside of our studio.…So, inside of our project,…we have a file called data dash processing,…which is where we'll be working.…So let's open that up.…And at the top of the file,…we load the tidyverse,…so we'll run that code with command enter.…

I'll minimize the file explorer…

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Released

10/6/2017

R is an incredibly powerful and widely used programming language for statistical analysis and data science. The "tidyverse" collects some of the most versatile R packages: ggplot2, dplyr, tidyr, readr, purrr, and tibble. The packages work in harmony to clean, process, model, and visualize data.

This course introduces the core concepts of the tidyverse as compared to the traditional base R. It focuses on the novice user and those unfamiliar with the pipe (%>%) operator. After covering these R basics, instructor Martin Hadley progresses to importing and filtering data from Excel, CSV, and SPSS files, and summarizing and tabulating data in the tidyverse. Then learn how to identify if data is too wide or long and convert it if necessary, and conduct nonstandard evaluation. By the end of the course, you should be able to integrate the tidyverse into your R workflow and leverage a variety of new tools for importing, filtering, visualizing, and modeling research and statistical data.